A method for determining the maximum gas leakage radius of tight gas wells

Abstract

The present invention discloses a method for determining the maximum gas leakage radius of a tight gas well, and belongs to the field of gas reservoir engineering. The method combines production dynamic data, first collects daily gas production and wellhead oil pressure and casing pressure data of the tight gas well, generates an actual production history curve, selects a model to produce a fitting curve, inverts to obtain equivalent parameters of reservoir properties, selects a model to generate a fitting curve, inverts to obtain equivalent parameters of reservoir properties, and calculates the maximum gas leakage radius according to the time when the maximum gas leakage radius occurs. The implementation case shows that the method can use the data commonly available in oil fields to realize the evaluation of the gas leakage radius, provide theoretical data support for the formulation of work systems, well network densification, and dynamic reserve evaluation, and guide the efficient development of gas fields.

Description

Technical Field

[0001] The present invention belongs to the field of gas reservoir engineering, and relates to a method for determining the maximum gas leakage radius of a tight gas well. Specifically, it relates to a method for determining the maximum gas leakage radius of a tight gas well based on oil reservoir engineering theory, gas reservoir engineering theory, and oil layer seepage mechanics, using only the daily production of the gas well and the wellhead oil casing pressure data, thereby avoiding the well shut-in pressure measurement operation and reducing the production loss. Background Art

[0002] In gas field production management, the gas well leakage radius is an important decision-making parameter. The leakage radius can be used to evaluate whether the gas reservoir has densification space. At the same time, the single well controlled reserves can be calculated through the leakage radius. The single well controlled reserves are the material basis for gas well production prediction. Therefore, accurately calculating the single well leakage radius parameter has important guiding significance.

[0003] Scholars at home and abroad have conducted in-depth research on the calculation of gas leakage radius, including professors and experts such as Ge Jiali, Chen Yuanqian, Liu Nengqiang, and Kong Xiangyan. In 1992, Chen Yuanqian derived the calculation formula of traditional gas leakage radius in "Derivation and Application of Two Formulas for Unstable Well Testing"; in 2002, Li Chuanliang studied the calculation method of detection radius in "Study of Calculation Formula of Oil Well Detection Radius"; in 2005, Gou Honggang studied a new flow-based gas leakage radius calculation method in "Research on New Method for Calculating Gas Well Influence Radius"; in 2006, Mao Wei of Daqing Oilfield published "Research on Calculation Method of Detection Radius Based on Flow" in Oil and Gas Geology and Recovery Factor, focusing on the study of the detection radius calculation method based on flow; in 2010, Li Chuanliang studied the calculation method of unidirectional flow gas leakage radius in "Calculation Formula of Planar Unidirectional Flow Detection Distance".

[0004] The above methods are all based on traditional material balance and well testing methods. Among them, the material balance method requires shutting down the well for pressure measurement, which not only affects the normal production of the gas field, but also often makes it difficult to obtain the true pressure value for low permeability gas reservoirs. The well testing method usually uses pressure drop or pressure recovery well testing to obtain the gas well leakage radius, but not every well has well testing data. At the same time, for tight gas reservoirs, due to the abnormally slow propagation speed of the pressure wave, the leakage boundary is often not detected during the pressure drop or pressure recovery test. As a result, the above methods have application limitations due to field data, which brings a huge burden to the dynamic monitoring of oil fields. In addition, due to many reasons such as economy and production maintenance, most wells cannot be tested for edge detection, resulting in the inability to obtain data on the control range of a single well. Summary of the invention

[0005] The purpose of the present invention is to provide a method for determining the maximum gas leakage radius of a tight gas well. Based on theories such as gas reservoir engineering and oil layer seepage mechanics, a method for calculating the maximum gas leakage radius based on variable production and variable pressure is established. The method provided by the present invention avoids the operation of shutting in the well for pressure measurement. It only uses the daily production of the gas well and the wellhead casing pressure data to obtain the reservoir physical property parameters through fitting inversion, and then clearly determines the time when the maximum gas leakage radius is reached, thereby calculating the maximum gas leakage radius of the tight gas well based on the seepage theory. The purpose of the present invention is achieved through the following specific technical solutions.

[0006] A method for determining a maximum gas leakage radius of a tight gas well comprises the following steps:

[0007] S1 collects daily gas production, wellhead oil pressure and casing pressure data of tight gas wells to generate actual production history curves;

[0008] S2 establishes a model to evaluate the expansion law of the gas leakage radius and inverts to obtain equivalent parameters of reservoir properties;

[0009] S3 draws the logarithmic curve of dimensionless production normalized pseudo-pressure and its derivative and dimensionless material balance time to determine the time when the maximum gas release radius is reached;

[0010] S4 calculates the maximum deflation radius according to the time when the maximum deflation radius is reached.

[0011] The present invention establishes a dense gas seepage model, reveals the dynamic expansion law of the gas leakage radius, studies the judgment basis of the pressure and its derivative curve when the maximum gas leakage radius is reached, and thus clarifies the time when the maximum gas leakage radius is reached; combines the seepage mechanics pressure expansion prediction model, and proposes a calculation method for the maximum gas leakage radius. Specifically, it includes the following contents.

[0012] The process of establishing the deflation radius expansion law evaluation model in step S2 is as follows:

[0013] Assume that the effective thickness of the tight gas reservoir is h, in meters, and at the initial moment, the pressure at all locations in the gas reservoir is p i Unit: MPa, Ψ 1D , 2D is the dimensionless pseudo pressure in the inner and outer zones, Ψ fD is the pseudo pressure in the fracture zone, r D is the dimensionless pressure transmission radius; there are two seepage zones with different physical property parameters in the reservoir, and the radius of the inner zone is r f , unit m, the permeability of the inner zone is K, unit mD, the mobility ratio of the inner and outer zones is M 12 ; Storage capacity ratio is ω 12 There is no additional pressure drop between the two seepage interfaces; the artificial fracture has infinite conductivity and the permeability is K f , unit is mD, crack half length is X f , unit is m, crack width is Wf , unit is m, considering the seepage of fluid in the crack; the air leakage radius is r e (t), unit: m; gas wells in tight gas reservoirs produce at a rate of q(t), unit: m 3 / d, the gas first flows from the reservoir into the fracture, and then from the fracture into the wellbore. After entering the artificial fracture, it is considered to have entered the wellbore.

[0014] The specific model diagram is as follows Figure 1 As shown in the figure, the inner area is the fracturing transformation area, the outer area is the original formation area, and the boundary of the outer area is the drainage flow boundary.

[0015] The mathematical model of unstable seepage in fractured vertical wells consists of two parts: formation seepage and hydraulic fracture flow. The flow in the fractures can be regarded as one-dimensional seepage, but from the perspective of the formation, the fractures are equivalent to a "huge wellbore" in the formation. On this basis, a mathematical model of dynamic boundary unstable seepage in radial composite fractured vertical wells in tight gas reservoirs is established:

[0016]

[0017] Since the width of the fracture is negligible relative to the reservoir scale, the fluid flow rate in the fracture width direction hardly changes and can be regarded as a constant, that is, the flow rate of the fluid flowing from the formation into the fracture. Since the permeability of the fracture is large, ignoring the influence of the fracture seepage change over time, a steady-state form can be obtained. Then the fracture mathematical model is obtained:

[0018]

[0019] According to the reservoir mathematical model, the solution of the seepage equation is:

[0020]

[0021] in,

[0022]

[0023]

[0024] E'=I1(a)K0(a)+I0(a)K1(a)

[0025] According to the point source function integration method, the reservoir pressure caused by the fracture can be obtained as:

[0026]

[0027] The integral method is used to solve the crack model and we get:

[0028]

[0029] The fracture is divided into n micro-element segments. Since each micro-element segment is very short, the flow rate in it can be considered to be a constant. Since the pressure of the reservoir and the fracture are equal on the fracture surface, based on the superposition principle and combined with the reservoir pressure solution, the pressure response of the jth micro-element segment satisfies:

[0030]

[0031] Based on the fracture pressure solution, the pressure difference between the wellbore and the jth microelement segment satisfies:

[0032]

[0033] Normalized equation for fracture flow:

[0034]

[0035] Using the principle of pressure superposition, the wellbore pressure solution can be obtained.

[0036]

[0037] Introducing dimensionless yield normalization pseudo-pressure RNP D and dimensionless material balance time t eD , the variable production rate is equivalent to the fixed production rate, and then the RNP of the radial composite dynamic boundary fracturing vertical well variable production model is obtained. D , RNP′ D ~t eD Double logarithmic curve. Among them, the dimensionless yield normalized pseudo pressure RNP D and material equilibrium time t eD for:

[0038]

[0039] Based on the above established model, the logarithmic curve of dimensionless production normalized pseudo-pressure and its derivative and dimensionless material balance time is drawn, such as Figure 2 As shown. It can be seen that with the increase of time, the gas leakage radius shows an increasing trend, and at a certain time point, the gas leakage radius reaches the maximum. This shows that in the production process of tight gas wells, the gas leakage range increases due to the propagation of pressure in the early stage, but due to the resistance effect, when the gas leakage radius reaches a certain range, the extrapolated boundary pressure difference is equivalent to the seepage resistance. At this time, the gas leakage radius has an inflection point, and the occurrence time is the time when the maximum gas leakage radius appears. Under different pressure conductivity conditions, this time appears between 0.3-2 years, which also shows that tight gas wells generally reach the maximum gas leakage radius within 0.3-2 years. At this time, the production dynamics enter a quasi-steady-state flow, showing an exponentially decreasing characteristic.

[0040] After determining the time to reach the maximum air leakage radius, the air leakage radius can be calculated based on the time in combination with the seepage mechanics theory. The formula is as follows:

[0041]

[0042] In the formula, r i is the maximum gas leakage radius, in m, t is the time to reach the maximum gas leakage radius, in hours, k is the equivalent permeability of the reservoir, in mD, Φ is the porosity, μ is the fluid viscosity, in mPa.s, C t is the fluid compressibility coefficient, MPa -1 .

[0043] The present invention aims at tight gas wells, constructs an evaluation model for the expansion law of the gas leakage radius, reveals the dynamic expansion law of the gas leakage radius, derives the material balance time when the maximum gas leakage radius is reached, and then combines the seepage theory to construct a method for calculating the gas leakage radius. The method provided by the present invention uses data such as the wellhead content and wellhead casing pressure data commonly found on site, avoids well shut-in operations, reduces production losses, and provides important parameter support and reference for gas field development and management. Specifically, it is embodied in: (1) a model for evaluating the expansion law of the gas leakage radius of tight gas wells is proposed; (2) the time when the tight gas well reaches the maximum gas leakage radius is determined using production dynamic data; (3) a method for calculating the gas leakage radius of tight gas wells is proposed. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the seepage physical model of the expansion law of the gas leakage radius;

[0045] Figure 2 This is a schematic diagram of the dynamic expansion law of the deflation radius;

[0046] Figure 3 A schematic flow chart of a method for determining the maximum gas leakage radius of a tight gas well provided by the present invention;

[0047] Figure 4 This is a schematic diagram of the production history curve for the implementation case;

[0048] Figure 5 Schematic diagram of double logarithmic curve of typical well pressure in implementation case. DETAILED DESCRIPTION

[0049] The technical solution of the present invention is described clearly and completely below in conjunction with the accompanying drawings of the specification. Obviously, the described implementation is only a part of the implementation of the present invention, not all of the implementations. Based on the implementation of the present invention, all other implementations obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] A tight gas reservoir has the characteristics of low production and low efficiency. During the flow of underground fluid, the pressure in the formation is constantly propagating outward, the external fluid is constantly supplied to the inner area, and the gas leakage radius is also constantly expanding. The gas leakage radius of each well is also an important factor affecting the production of the gas well. In order to correctly evaluate the dynamic reserves and gas well production, determine the remaining reserve area, and reduce the risk of well layout, it is necessary to conduct research on the expansion law of the gas leakage radius to provide data support for optimizing the fracturing transformation plan and improving the degree of reserve utilization. The process of determining the maximum gas leakage radius is as follows: Figure 3 shown.

[0051] (1) Typical gas well production characteristics

[0052] The daily gas production of the tight gas reservoir gradually decreases over time, the production also shows an inflection point, and the bottom hole pressure also shows a rapid depletion feature. In order to clarify the cause of the gas well decline, it is necessary to determine the gas well leakage radius according to the production dynamics, such as Figure 4 shown.

[0053] First, the production dynamic analysis fitting method is used to invert and obtain the basic physical property parameters of the reservoir, which will be used as the input parameter for the calculation of the gas leakage radius to achieve the evaluation of the maximum gas leakage radius. The interpretation results of typical wells are shown in Table 1.

[0054] Table 1. Fitting parameter results of typical wells

[0055]

[0056] (2) Determination of the time when the maximum leakage radius occurs

[0057] The variable production and variable pressure seepage model is established, and the actual data is processed by double logarithmic curves, such as Figure 5 As shown in the figure, it can be seen that the pressure derivative curve shows an upward feature at 1000 hours, and this time point is the time when the maximum leak radius is reached.

[0058] (3) Calculation of leak radius

[0059] Based on the determination of the basic physical properties of the reservoir, combined with the time of occurrence of the maximum gas leakage radius, the maximum gas leakage radius can be calculated by applying the formula. This implementation case completed the determination of the gas leakage radius of 10 wells in the gas reservoir, as shown in Table 2.

[0060] Table 2 Evaluation results of gas leakage radius of typical wells

[0061]

[0062] As can be seen from Table 2, the larger the fracture half-length and matrix permeability, the larger the gas leakage radius. In order to achieve stable production of gas wells, it is recommended to use repeated fracturing technology to expand the gas leakage radius for gas wells with a small gas leakage radius, thereby increasing the utilization range and sustainable production of gas wells.

[0063] Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention. The protection scope of the present invention is defined by the claims and their equivalent technical solutions.

Claims

1. A method for determining the maximum gas leakage radius of a tight gas well, characterized in that: The following steps are involved: S1 collects daily gas production, wellhead oil pressure and casing pressure data of tight gas wells to generate actual production history curves; S2 establishes a model to evaluate the expansion law of the gas leakage radius and inverts to obtain equivalent parameters of reservoir properties; S3 draws the logarithmic curve of dimensionless production normalized pseudo-pressure and its derivative and dimensionless material balance time to determine the time when the maximum gas release radius is reached; S4 calculates the maximum deflation radius according to the time when the maximum deflation radius is reached.

2. The method according to claim 1, characterized in that The specific process of step S2 is: Assume that the effective thickness of the tight gas reservoir is h, in meters, and at the initial moment, the pressure at all locations in the gas reservoir is p i Unit: MPa, Ψ 1D , 2D is the dimensionless pseudo pressure in the inner and outer zones, Ψ fD is the pseudo pressure in the fracture zone, r D is the dimensionless pressure transmission radius; there are two seepage zones with different physical property parameters in the reservoir, and the radius of the inner zone is r f , unit m, the permeability of the inner zone is K, unit mD, the mobility ratio of the inner and outer zones is M 12 ; Storage capacity ratio is ω 12 There is no additional pressure drop between the two seepage interfaces; the artificial fracture has infinite conductivity and the permeability is K f , unit is mD, crack half length is X f , unit is m, crack width is W f , unit is m, considering the seepage of fluid in the crack; the air leakage radius is r e (t), unit: m; gas wells in tight gas reservoirs produce at a rate of q(t), unit: m 3 / d, the gas first flows from the reservoir into the fracture, then from the fracture into the wellbore, and after entering the artificial fracture, it is considered to have entered the wellbore; The mathematical model of dynamic boundary instability seepage in radial composite fractured vertical wells in tight gas reservoirs is: The mathematical model of the crack is: The solution of the seepage equation is: in, E'=I1(a)K0(a)+I0(a)K1(a) According to the point source function integration method, the reservoir pressure caused by fractures is: The integral method is used to solve the crack model and we get: The crack is divided into n micro-elements, and the pressure response of the j-th micro-element satisfies: Based on the fracture pressure solution, the pressure difference between the wellbore and the jth microelement segment satisfies: Normalized equation for fracture flow: Using the principle of pressure superposition, the wellbore pressure solution is obtained.

3. The method according to claim 2, characterized in that Dimensionless yield normalized pseudo-pressure RNP D and its derivative RNP D ′ and material equilibrium time t eD They are:

4. The method according to claim 3, characterized in that The maximum deflation radius is calculated as follows: In the formula, r i is the maximum gas leakage radius, t is the time to reach the maximum gas leakage radius, k is the equivalent permeability of the reservoir, Φ is the porosity, μ is the fluid viscosity, C t is the fluid compressibility coefficient.

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